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→Stability of results 结果的稳定性
It is important to obtain some indication about how generalizable the results are. While this is often difficult to check, one can look at the stability of the results. Are the results reliable and reproducible? There are two main ways of doing that.
It is important to obtain some indication about how generalizable the results are. While this is often difficult to check, one can look at the stability of the results. Are the results reliable and reproducible? There are two main ways of doing that.
得到一些说明这些结果有多么普遍的指标是重要的。虽然普遍性通常很难检验，但可以表示结果的稳定性的一些信息。有两种主要的方法来保证结果的可靠和可重复性。
* ''[[Cross-validation (statistics)|Cross-validation]]''. By splitting the data into multiple parts, we can check if an analysis (like a fitted model) based on one part of the data generalizes to another part of the data as well. Cross-validation is generally inappropriate, though, if there are correlations within the data, e.g. with [[panel data]]. Hence other methods of validation sometimes need to be used. For more on this topic, see [[statistical model validation]].
* ''[[Cross-validation (statistics)|Cross-validation]]''. By splitting the data into multiple parts, we can check if an analysis (like a fitted model) based on one part of the data generalizes to another part of the data as well. Cross-validation is generally inappropriate, though, if there are correlations within the data, e.g. with [[panel data]]. Hence other methods of validation sometimes need to be used. For more on this topic, see [[statistical model validation]].